Myusic: a Content-based Music Recommender System based on eVSM and Social Media

This paper presents Myusic, a platform that leverages social media to produce content-based music recommendations. The design of the platform is based on the insight that user preferences in music can be extracted by mining Facebook profiles, thus providing a novel and effective way to sift in large music databases and overcome the cold-start problem as well. The content-based recommendation model implemented in Myusic is eVSM [4], an enhanced version of the vector space model based on distributional models, Random Indexing and Quantum Negation. The effectiveness of the platform is evaluated through a preliminary user study performed on a sample of 50 persons. The results showed that 74% of users actually prefer recommendations computed by social mediabased profiles with respect to those computed by a simple heuristic based on the popularity of artists, and confirmed the usefulness of performing user studies because of the different outcomes they can provide with respect to offline experiments.